反向传播
蚁群优化算法
可靠性(半导体)
MOSFET
人工神经网络
热阻
结温
材料科学
分类
电子工程
计算机科学
晶体管
工程类
热的
人工智能
电气工程
电压
功率(物理)
气象学
物理
程序设计语言
量子力学
作者
Jing Jiang,Wei Chen,Yichen Qian,Abdulmelik Husen Meda,Xuejun Fan,Guoqi Zhang,Jiajie Fan
出处
期刊:IEEE Transactions on Components, Packaging and Manufacturing Technology
[Institute of Electrical and Electronics Engineers]
日期:2023-04-01
卷期号:13 (4): 481-488
被引量:3
标识
DOI:10.1109/tcpmt.2023.3267411
摘要
Considerable advancements in power semiconductor devices have resulted in such devices being increasingly adopted in applications of energy generation, conversion, and transmission. Hence, we proposed a fan-out panel-level packaging (FOPLP) design for 30-V Si-based metal–oxide–semiconductor field-effect transistor (MOSFET). To achieve superior reliability of packaging, we applied the nondominated sorting genetic algorithm with elitist strategy (NSGA-II) and ant colony optimization–backpropagation neural network (ACO–BPNN) to optimize the design of redistribution layer (RDL) in FOPLP. We first quantified the thermal resistance and thermomechanical coupling stress of the designed package under thermal cycling loading. Next, NSGA-II and ACO–BPNN were used to optimize the size of the RDL blind via. Finally, the effectiveness of the proposed reliability optimization methods was verified by performing thermal shock reliability aging tests on the prepared devices.
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